Paper Info
Title
New complexity analysis of a Mehrotra-type predictor–corrector algorithm for semidefinite programming
Abstract
In this paper, we propose a new Mehrotra-type predictor–corrector interior-point algorithm for semidefinite programming. This algorithm is an extension of the variant of Mehrotra-type algorithm that was proposed by Salahi et al. [On Mehrotra-type predictor–corrector algorithms, SIAM J. Optim. 18 2007, pp. 1377–1397] for linear programming problems. We modify the step sizes lightly in the predictor step of Koulaei and Terlaky [On the complexity analysis of a Mehrotra-type primal–dual feasible algorithm for semidefinite optimization, Optim. Methods Softw. 25 2010, pp. 467–485]. In such a way, we obtain OnlogTrX0S0/ϵ iteration complexity of the algorithm, where X0, y0, S0 is the initial feasible point and ϵ is the required precision.
Year
DOI
Venue
2013
10.1080/10556788.2012.679270
Optimization Methods and Software
Keywords
Field
DocType
mehrotra-type primal,corrector interior-point algorithm,mehrotra-type predictor,complexity analysis,siam j. optim,corrector algorithm,mehrotra-type algorithm,new complexity analysis,new mehrotra-type predictor,dual feasible algorithm,predictor step,semidefinite programming,interior point methods,linear program,interior point method
Discrete mathematics,Mathematical optimization,Algorithm,Linear programming,Polynomial complexity,Large margin nearest neighbor,Semidefinite embedding,Interior point method,Predictor–corrector method,Criss-cross algorithm,Mathematics,Semidefinite programming
Journal
Volume
Issue
ISSN
28
6
1055-6788
Citations 
PageRank 
References 
3
0.40
16
Authors
3
Name
Order
Citations
PageRank
Hongwei Liu17812.29
Changhe Liu2383.62
Ximei Yang3262.34